Cunefare, D;
Huckenpahler, AL;
Patterson, EJ;
Dubra, A;
Carroll, J;
Farsiu, S;
(2019)
RAC-CNN: multimodal deep learning based automatic detection and classification of rod and cone photoreceptors in adaptive optics scanning light ophthalmoscope images.
Biomedical Optics Express
, 10
(8)
pp. 3815-3832.
10.1364/boe.10.003815.
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Abstract
Quantification of the human rod and cone photoreceptor mosaic in adaptive optics scanning light ophthalmoscope (AOSLO) images is useful for the study of various retinal pathologies. Subjective and time-consuming manual grading has remained the gold standard for evaluating these images, with no well validated automatic methods for detecting individual rods having been developed. We present a novel deep learning based automatic method, called the rod and cone CNN (RAC-CNN), for detecting and classifying rods and cones in multimodal AOSLO images. We test our method on images from healthy subjects as well as subjects with achromatopsia over a range of retinal eccentricities. We show that our method is on par with human grading for detecting rods and cones.
Type: | Article |
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Title: | RAC-CNN: multimodal deep learning based automatic detection and classification of rod and cone photoreceptors in adaptive optics scanning light ophthalmoscope images |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1364/boe.10.003815 |
Publisher version: | https://doi.org/10.1364/BOE.10.003815 |
Language: | English |
Additional information: | © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement (https://doi.org/10.1364/OA_License_v1). |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
URI: | https://discovery.ucl.ac.uk/id/eprint/10086711 |
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